Identifying latent patterns in undergraduate Students’ programming profiles
Abstract This study aims to explore and reveal profiling patterns in the measurement of cognitive and noncognitivecharacteristics of undergraduate students’ programming performances. Spatial skills, workingmemory, perceived programming self-efficacy, mathematics scores, and academic grade point aver...
Ausführliche Beschreibung
Autor*in: |
Altun, Arif [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2015 |
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Anmerkung: |
© Altun and Mazman. 2015 |
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Übergeordnetes Werk: |
Enthalten in: Smart Learning Environments - Berlin : SpringerOpen, 2014, 2(2015), 1 vom: 17. Sept. |
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Übergeordnetes Werk: |
volume:2 ; year:2015 ; number:1 ; day:17 ; month:09 |
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DOI / URN: |
10.1186/s40561-015-0020-0 |
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SPR036664057 |
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10.1186/s40561-015-0020-0 doi (DE-627)SPR036664057 (SPR)s40561-015-0020-0-e DE-627 ger DE-627 rakwb eng Altun, Arif verfasserin aut Identifying latent patterns in undergraduate Students’ programming profiles 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Altun and Mazman. 2015 Abstract This study aims to explore and reveal profiling patterns in the measurement of cognitive and noncognitivecharacteristics of undergraduate students’ programming performances. Spatial skills, workingmemory, perceived programming self-efficacy, mathematics scores, and academic grade point averagescores were taken indicative variables to be explored. Participants of the study are 100 undergraduatestudents registered to the Programming-I course at two different universities. The data were analyzedthrough multi-dimensional profile analysis. The result of the multidimensional scaling analysis indicated twodifferent profiles for the two groups: high and low programming performance groups. For both groups,relationship between the most similar variables was found to be verbal memory, mathematics achievementand perceived programming self-efficacy. The results indicated that there was a relatively similarrelationship between visual-spatial memory and spatial orientation skills in the low-performance group,while mental rotation skill was significantly different than the other variables. It was noted that two profiles forhigh- and low-performance groups were quite different in terms of mental rotation skill. It was also found that spatial orientation, visual-spatial memory and mental rotation performances were all different from eachother, and from the other three variables in the group with high programming performance. The mostdefinitive variables for low- and high-performance groups were self-efficacy, verbal memory andmathematics achievement. This study revealed that only verbal memory was the determinant variable inboth groups for working memory. Mental Rotation (dpeaa)DE-He213 Verbal Memory (dpeaa)DE-He213 Work Memory Capacity (dpeaa)DE-He213 Mathematics Achievement (dpeaa)DE-He213 Programming Performance (dpeaa)DE-He213 Mazman, Sacide Guzin aut Enthalten in Smart Learning Environments Berlin : SpringerOpen, 2014 2(2015), 1 vom: 17. Sept. (DE-627)805638547 (DE-600)2800615-X 2196-7091 nnns volume:2 year:2015 number:1 day:17 month:09 https://dx.doi.org/10.1186/s40561-015-0020-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2044 GBV_ILN_2086 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2015 1 17 09 |
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10.1186/s40561-015-0020-0 doi (DE-627)SPR036664057 (SPR)s40561-015-0020-0-e DE-627 ger DE-627 rakwb eng Altun, Arif verfasserin aut Identifying latent patterns in undergraduate Students’ programming profiles 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Altun and Mazman. 2015 Abstract This study aims to explore and reveal profiling patterns in the measurement of cognitive and noncognitivecharacteristics of undergraduate students’ programming performances. Spatial skills, workingmemory, perceived programming self-efficacy, mathematics scores, and academic grade point averagescores were taken indicative variables to be explored. Participants of the study are 100 undergraduatestudents registered to the Programming-I course at two different universities. The data were analyzedthrough multi-dimensional profile analysis. The result of the multidimensional scaling analysis indicated twodifferent profiles for the two groups: high and low programming performance groups. For both groups,relationship between the most similar variables was found to be verbal memory, mathematics achievementand perceived programming self-efficacy. The results indicated that there was a relatively similarrelationship between visual-spatial memory and spatial orientation skills in the low-performance group,while mental rotation skill was significantly different than the other variables. It was noted that two profiles forhigh- and low-performance groups were quite different in terms of mental rotation skill. It was also found that spatial orientation, visual-spatial memory and mental rotation performances were all different from eachother, and from the other three variables in the group with high programming performance. The mostdefinitive variables for low- and high-performance groups were self-efficacy, verbal memory andmathematics achievement. This study revealed that only verbal memory was the determinant variable inboth groups for working memory. Mental Rotation (dpeaa)DE-He213 Verbal Memory (dpeaa)DE-He213 Work Memory Capacity (dpeaa)DE-He213 Mathematics Achievement (dpeaa)DE-He213 Programming Performance (dpeaa)DE-He213 Mazman, Sacide Guzin aut Enthalten in Smart Learning Environments Berlin : SpringerOpen, 2014 2(2015), 1 vom: 17. Sept. (DE-627)805638547 (DE-600)2800615-X 2196-7091 nnns volume:2 year:2015 number:1 day:17 month:09 https://dx.doi.org/10.1186/s40561-015-0020-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2044 GBV_ILN_2086 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2015 1 17 09 |
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10.1186/s40561-015-0020-0 doi (DE-627)SPR036664057 (SPR)s40561-015-0020-0-e DE-627 ger DE-627 rakwb eng Altun, Arif verfasserin aut Identifying latent patterns in undergraduate Students’ programming profiles 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Altun and Mazman. 2015 Abstract This study aims to explore and reveal profiling patterns in the measurement of cognitive and noncognitivecharacteristics of undergraduate students’ programming performances. Spatial skills, workingmemory, perceived programming self-efficacy, mathematics scores, and academic grade point averagescores were taken indicative variables to be explored. Participants of the study are 100 undergraduatestudents registered to the Programming-I course at two different universities. The data were analyzedthrough multi-dimensional profile analysis. The result of the multidimensional scaling analysis indicated twodifferent profiles for the two groups: high and low programming performance groups. For both groups,relationship between the most similar variables was found to be verbal memory, mathematics achievementand perceived programming self-efficacy. The results indicated that there was a relatively similarrelationship between visual-spatial memory and spatial orientation skills in the low-performance group,while mental rotation skill was significantly different than the other variables. It was noted that two profiles forhigh- and low-performance groups were quite different in terms of mental rotation skill. It was also found that spatial orientation, visual-spatial memory and mental rotation performances were all different from eachother, and from the other three variables in the group with high programming performance. The mostdefinitive variables for low- and high-performance groups were self-efficacy, verbal memory andmathematics achievement. This study revealed that only verbal memory was the determinant variable inboth groups for working memory. Mental Rotation (dpeaa)DE-He213 Verbal Memory (dpeaa)DE-He213 Work Memory Capacity (dpeaa)DE-He213 Mathematics Achievement (dpeaa)DE-He213 Programming Performance (dpeaa)DE-He213 Mazman, Sacide Guzin aut Enthalten in Smart Learning Environments Berlin : SpringerOpen, 2014 2(2015), 1 vom: 17. Sept. (DE-627)805638547 (DE-600)2800615-X 2196-7091 nnns volume:2 year:2015 number:1 day:17 month:09 https://dx.doi.org/10.1186/s40561-015-0020-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2044 GBV_ILN_2086 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2015 1 17 09 |
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10.1186/s40561-015-0020-0 doi (DE-627)SPR036664057 (SPR)s40561-015-0020-0-e DE-627 ger DE-627 rakwb eng Altun, Arif verfasserin aut Identifying latent patterns in undergraduate Students’ programming profiles 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Altun and Mazman. 2015 Abstract This study aims to explore and reveal profiling patterns in the measurement of cognitive and noncognitivecharacteristics of undergraduate students’ programming performances. Spatial skills, workingmemory, perceived programming self-efficacy, mathematics scores, and academic grade point averagescores were taken indicative variables to be explored. Participants of the study are 100 undergraduatestudents registered to the Programming-I course at two different universities. The data were analyzedthrough multi-dimensional profile analysis. The result of the multidimensional scaling analysis indicated twodifferent profiles for the two groups: high and low programming performance groups. For both groups,relationship between the most similar variables was found to be verbal memory, mathematics achievementand perceived programming self-efficacy. The results indicated that there was a relatively similarrelationship between visual-spatial memory and spatial orientation skills in the low-performance group,while mental rotation skill was significantly different than the other variables. It was noted that two profiles forhigh- and low-performance groups were quite different in terms of mental rotation skill. It was also found that spatial orientation, visual-spatial memory and mental rotation performances were all different from eachother, and from the other three variables in the group with high programming performance. The mostdefinitive variables for low- and high-performance groups were self-efficacy, verbal memory andmathematics achievement. This study revealed that only verbal memory was the determinant variable inboth groups for working memory. Mental Rotation (dpeaa)DE-He213 Verbal Memory (dpeaa)DE-He213 Work Memory Capacity (dpeaa)DE-He213 Mathematics Achievement (dpeaa)DE-He213 Programming Performance (dpeaa)DE-He213 Mazman, Sacide Guzin aut Enthalten in Smart Learning Environments Berlin : SpringerOpen, 2014 2(2015), 1 vom: 17. Sept. (DE-627)805638547 (DE-600)2800615-X 2196-7091 nnns volume:2 year:2015 number:1 day:17 month:09 https://dx.doi.org/10.1186/s40561-015-0020-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2044 GBV_ILN_2086 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2015 1 17 09 |
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10.1186/s40561-015-0020-0 doi (DE-627)SPR036664057 (SPR)s40561-015-0020-0-e DE-627 ger DE-627 rakwb eng Altun, Arif verfasserin aut Identifying latent patterns in undergraduate Students’ programming profiles 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Altun and Mazman. 2015 Abstract This study aims to explore and reveal profiling patterns in the measurement of cognitive and noncognitivecharacteristics of undergraduate students’ programming performances. Spatial skills, workingmemory, perceived programming self-efficacy, mathematics scores, and academic grade point averagescores were taken indicative variables to be explored. Participants of the study are 100 undergraduatestudents registered to the Programming-I course at two different universities. The data were analyzedthrough multi-dimensional profile analysis. The result of the multidimensional scaling analysis indicated twodifferent profiles for the two groups: high and low programming performance groups. For both groups,relationship between the most similar variables was found to be verbal memory, mathematics achievementand perceived programming self-efficacy. The results indicated that there was a relatively similarrelationship between visual-spatial memory and spatial orientation skills in the low-performance group,while mental rotation skill was significantly different than the other variables. It was noted that two profiles forhigh- and low-performance groups were quite different in terms of mental rotation skill. It was also found that spatial orientation, visual-spatial memory and mental rotation performances were all different from eachother, and from the other three variables in the group with high programming performance. The mostdefinitive variables for low- and high-performance groups were self-efficacy, verbal memory andmathematics achievement. This study revealed that only verbal memory was the determinant variable inboth groups for working memory. Mental Rotation (dpeaa)DE-He213 Verbal Memory (dpeaa)DE-He213 Work Memory Capacity (dpeaa)DE-He213 Mathematics Achievement (dpeaa)DE-He213 Programming Performance (dpeaa)DE-He213 Mazman, Sacide Guzin aut Enthalten in Smart Learning Environments Berlin : SpringerOpen, 2014 2(2015), 1 vom: 17. Sept. (DE-627)805638547 (DE-600)2800615-X 2196-7091 nnns volume:2 year:2015 number:1 day:17 month:09 https://dx.doi.org/10.1186/s40561-015-0020-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2044 GBV_ILN_2086 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2015 1 17 09 |
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Altun, Arif misc Mental Rotation misc Verbal Memory misc Work Memory Capacity misc Mathematics Achievement misc Programming Performance Identifying latent patterns in undergraduate Students’ programming profiles |
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identifying latent patterns in undergraduate students’ programming profiles |
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Identifying latent patterns in undergraduate Students’ programming profiles |
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Abstract This study aims to explore and reveal profiling patterns in the measurement of cognitive and noncognitivecharacteristics of undergraduate students’ programming performances. Spatial skills, workingmemory, perceived programming self-efficacy, mathematics scores, and academic grade point averagescores were taken indicative variables to be explored. Participants of the study are 100 undergraduatestudents registered to the Programming-I course at two different universities. The data were analyzedthrough multi-dimensional profile analysis. The result of the multidimensional scaling analysis indicated twodifferent profiles for the two groups: high and low programming performance groups. For both groups,relationship between the most similar variables was found to be verbal memory, mathematics achievementand perceived programming self-efficacy. The results indicated that there was a relatively similarrelationship between visual-spatial memory and spatial orientation skills in the low-performance group,while mental rotation skill was significantly different than the other variables. It was noted that two profiles forhigh- and low-performance groups were quite different in terms of mental rotation skill. It was also found that spatial orientation, visual-spatial memory and mental rotation performances were all different from eachother, and from the other three variables in the group with high programming performance. The mostdefinitive variables for low- and high-performance groups were self-efficacy, verbal memory andmathematics achievement. This study revealed that only verbal memory was the determinant variable inboth groups for working memory. © Altun and Mazman. 2015 |
abstractGer |
Abstract This study aims to explore and reveal profiling patterns in the measurement of cognitive and noncognitivecharacteristics of undergraduate students’ programming performances. Spatial skills, workingmemory, perceived programming self-efficacy, mathematics scores, and academic grade point averagescores were taken indicative variables to be explored. Participants of the study are 100 undergraduatestudents registered to the Programming-I course at two different universities. The data were analyzedthrough multi-dimensional profile analysis. The result of the multidimensional scaling analysis indicated twodifferent profiles for the two groups: high and low programming performance groups. For both groups,relationship between the most similar variables was found to be verbal memory, mathematics achievementand perceived programming self-efficacy. The results indicated that there was a relatively similarrelationship between visual-spatial memory and spatial orientation skills in the low-performance group,while mental rotation skill was significantly different than the other variables. It was noted that two profiles forhigh- and low-performance groups were quite different in terms of mental rotation skill. It was also found that spatial orientation, visual-spatial memory and mental rotation performances were all different from eachother, and from the other three variables in the group with high programming performance. The mostdefinitive variables for low- and high-performance groups were self-efficacy, verbal memory andmathematics achievement. This study revealed that only verbal memory was the determinant variable inboth groups for working memory. © Altun and Mazman. 2015 |
abstract_unstemmed |
Abstract This study aims to explore and reveal profiling patterns in the measurement of cognitive and noncognitivecharacteristics of undergraduate students’ programming performances. Spatial skills, workingmemory, perceived programming self-efficacy, mathematics scores, and academic grade point averagescores were taken indicative variables to be explored. Participants of the study are 100 undergraduatestudents registered to the Programming-I course at two different universities. The data were analyzedthrough multi-dimensional profile analysis. The result of the multidimensional scaling analysis indicated twodifferent profiles for the two groups: high and low programming performance groups. For both groups,relationship between the most similar variables was found to be verbal memory, mathematics achievementand perceived programming self-efficacy. The results indicated that there was a relatively similarrelationship between visual-spatial memory and spatial orientation skills in the low-performance group,while mental rotation skill was significantly different than the other variables. It was noted that two profiles forhigh- and low-performance groups were quite different in terms of mental rotation skill. It was also found that spatial orientation, visual-spatial memory and mental rotation performances were all different from eachother, and from the other three variables in the group with high programming performance. The mostdefinitive variables for low- and high-performance groups were self-efficacy, verbal memory andmathematics achievement. This study revealed that only verbal memory was the determinant variable inboth groups for working memory. © Altun and Mazman. 2015 |
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score |
7.3994884 |